Predicting cancer relapse following lung stereotactic radiotherapy: an external validation study using real-world evidence.

NSCLC biomarker-by-treatment interactions external validation image-based data mining local relapse personalized medicine real world data stereotactic ablative body radiotherapy (SABR)

Journal

Frontiers in oncology
ISSN: 2234-943X
Titre abrégé: Front Oncol
Pays: Switzerland
ID NLM: 101568867

Informations de publication

Date de publication:
2023
Historique:
received: 01 02 2023
accepted: 27 06 2023
medline: 28 7 2023
pubmed: 28 7 2023
entrez: 28 7 2023
Statut: epublish

Résumé

For patients receiving lung stereotactic ablative radiotherapy (SABR), evidence suggests that high peritumor density predicts an increased risk of microscopic disease (MDE) and local-regional failure, but only if there is low or heterogenous 199 patients treated in a routine setting were collated from a single institution for training, and 76 patients from an external institution for validation. Three density metrics (mean, 90 Local relapse occurred at a rate of 6.5% in the training cohort, and 18% in the validation cohort, which included larger and more centrally located tumors. High peritumor density in combination with high dose variability (0.5 - 1.6cm) predicts LR. No interactions predicted RF. The LR interaction improved the predictive ability compared to using clinical variables alone (optimism-adjusted C-index; 0.82 vs 0.76). Re-fitting model coefficients in external data confirmed the importance of this interaction (C-index; 0.86 vs 0.76). Dose variability in the 0.5-1.6 cm annular region strongly correlates with heterogeneity inside the target volume (SD; ρ = 0.53 training, ρ = 0.65 validation). In these real-world cohorts, the combination of relatively high peritumor density and high dose variability predicts increase in LR, but not RF, following lung SABR. This external validation justifies potential use of the model to increase low-dose CTV margins for high-risk patients.

Identifiants

pubmed: 37503315
doi: 10.3389/fonc.2023.1156389
pmc: PMC10369005
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1156389

Subventions

Organisme : NCI NIH HHS
ID : P30 CA008748
Pays : United States

Informations de copyright

Copyright © 2023 Davey, Thor, van Herk, Faivre-Finn, Rimner, Deasy and McWilliam.

Déclaration de conflit d'intérêts

AR: Research funding from AstraZeneca, Merck, Pfizer, Boehringer Ingelheim, and Varian Medical Systems. Consulting fees/advisory boards for AstraZeneca, Merck and MoreHealth. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Références

Phys Med. 2020 Jan;69:192-204
pubmed: 31923757
Cancer. 2010 May 15;116(10):2390-400
pubmed: 20225332
Am J Clin Oncol. 1982 Dec;5(6):649-55
pubmed: 7165009
Radiother Oncol. 2016 Apr;119(1):123-8
pubmed: 26993415
BMC Med Res Methodol. 2013 Mar 06;13:33
pubmed: 23496923
Ann Oncol. 2017 Jul 1;28(suppl_4):iv1-iv21
pubmed: 28881918
Lancet Oncol. 2012 Apr;13(4):e169-77
pubmed: 22469127
Med Phys. 2021 Jun;48(6):3234-3242
pubmed: 33772803
Radiother Oncol. 2013 Oct;109(1):13-20
pubmed: 24183066
Br J Radiol. 2016 Aug;89(1064):20160146
pubmed: 27245138
Radiother Oncol. 2018 Sep;128(3):513-519
pubmed: 29801721
Clin Cancer Res. 2017 Sep 15;23(18):5469-5479
pubmed: 28539466
Med Phys. 2010 Aug;37(8):4078-101
pubmed: 20879569
Cancer. 1990 Dec 15;66(12):2498-502
pubmed: 2249190
Radiother Oncol. 2015 Mar;114(3):361-6
pubmed: 25770872
J Clin Oncol. 2017 May 1;35(13):1395-1402
pubmed: 28301264
Lancet Oncol. 2012 Aug;13(8):802-9
pubmed: 22727222
Int J Radiat Oncol Biol Phys. 2017 Jan 1;97(1):138-145
pubmed: 27839909
Phys Imaging Radiat Oncol. 2020 Apr;14:87-94
pubmed: 32582869
Clin Lung Cancer. 2016 May;17(3):177-183.e2
pubmed: 26602271
Radiother Oncol. 2014 Mar;110(3):511-6
pubmed: 24560765
Radiother Oncol. 2013 Oct;109(1):26-31
pubmed: 24100151
Int J Radiat Oncol Biol Phys. 2020 Jul 1;107(3):579-586
pubmed: 32188579
Int J Radiat Oncol Biol Phys. 2012 Jan 1;82(1):448-56
pubmed: 20971575
Phys Med Biol. 2020 Oct 30;65(21):215001
pubmed: 32693397
J Thorac Oncol. 2017 Mar;12(3):547-555
pubmed: 28126325
Med Phys. 2021 Feb;48(2):724-732
pubmed: 33290579
Clin Oncol (R Coll Radiol). 2017 Dec;29(12):814-817
pubmed: 28781199
Strahlenther Onkol. 2019 Mar;195(3):193-198
pubmed: 30649567
Int J Radiat Oncol Biol Phys. 2014 Sep 1;90(1):209-15
pubmed: 24997639
Sci Rep. 2018 Aug 29;8(1):13047
pubmed: 30158540
Front Oncol. 2022 Mar 09;12:838155
pubmed: 35356210
Cancer Treat Rev. 2016 Nov;50:240-246
pubmed: 27768919
J Clin Oncol. 2009 Aug 20;27(24):4027-34
pubmed: 19597023
Cancer. 2017 Aug 15;123(16):3031-3039
pubmed: 28346656
Phys Med Biol. 2021 May 24;66(11):
pubmed: 33882470
J Clin Oncol. 2002 May 15;20(10):2495-9
pubmed: 12011127
Phys Med. 2016 Apr;32(4):600-6
pubmed: 27061871
Int J Radiat Oncol Biol Phys. 2012 Nov 1;84(3):e379-84
pubmed: 22999272

Auteurs

Angela Davey (A)

Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom.

Maria Thor (M)

Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States.

Marcel van Herk (M)

Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom.

Corinne Faivre-Finn (C)

Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom.
Department of Clinical Oncology, The Christie NHS Foundation Trust, Manchester, United Kingdom.

Andreas Rimner (A)

Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States.

Joseph O Deasy (JO)

Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States.

Alan McWilliam (A)

Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom.

Classifications MeSH